84 citations · 171 across the 10 of their papers we have counts for
4 papers · 1 filter
Boosting K-means for Big Data by Fusing Data Streaming with Global Optimization
Ravil Mussabayev, Rustam Mussabayev
K-means clustering is a cornerstone of data mining, but its efficiency deteriorates when confronted with massive datasets. To address this limitation, we propose a novel heuristic…
Variable Landscape Search: A Novel Metaheuristic Paradigm for Unlocking Hidden Dimensions in Global Optimization
Rustam Mussabayev, Ravil Mussabayev
This paper presents the Variable Landscape Search (VLS), a novel metaheuristic designed to globally optimize complex problems by dynamically altering the objective function landsca…
Superior Parallel Big Data Clustering through Competitive Stochastic Sample Size Optimization in Big-means
Rustam Mussabayev, Ravil Mussabayev
This paper introduces a novel K-means clustering algorithm, an advancement on the conventional Big-means methodology. The proposed method efficiently integrates parallel processing…
Finetuning Large Language Models for Vulnerability Detection
Alexey Shestov, Rodion Levichev, Ravil Mussabayev +3
This paper presents the results of finetuning large language models (LLMs) for the task of detecting vulnerabilities in source code. We leverage WizardCoder, a recent improvement o…